Browsing by Author "Maciocco Gavino"

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Health Inequalities Within a Nation: a Review of Two New Theories
(Uganda Martyrs University, Department of Health Sciences, 2003-12) Maciocco Gavino
What policies and values influence inequalities of health of individuals and populations? There are two main interpretations: a “materialist”, and “psycho-social” (Coburn D, 2000). It is suggested that the more a regime is neo-liberal, the bigger are the inequalities in income. The more a society is market oriented, the smaller is the trust and social-cohesion. It has been known for a long time that there is an inverse proportion between the socio-economic conditions and the state of health of a population. In the majority of industrialised countries health inequality has not been reduced despite the improvement of welfare, as reflected by, among others, life expectancy. The latest report on health inequality in England (Department of Health, London, 1998) analyses among other things the mortality rate over the last 30 years, through all causes and a series of specific causes, correlating it with six different population groups selected according to kind of work they do. Figure 1 gives the mortality rate from all causes among the male population of 20-64 years, taken from the years 197072, 1979-83 and 1991-93. The graph shows that: a) the mortality rates of the six social classes register an order that is inversely proportional to the level of social class; b) clear-cut differences are seen between professionals and technician-managers, who register the lowest mortality rates, specialised and semi-specialised, who occupy a middle position; and the non-specialised who have the highest mortality rates; c) in the space of 20 years the mortality rates diminished in all the classes, but the gap between the richer and poorer classes widened considerably; between the early 70s and 90s the mortality rates fell by 40% in classes I and II, by 30% in classes IIIN, IIIM and IV, and only by 10% in class V. These growing differences in state of health among the various social groups are also reflected in the specific causes of death: coronary disease, stroke, lung cancer, and suicide among the men, and respiratory diseases, coronary disease and lung cancer among the women. These differences in the mortality rates are reflected in the differences in life expectancy at birth between rich and poor classes: by five years among the men (75 instead of 70), by three years for the women (80 instead of 77). Similar tendencies are found in the USA where, analysing the state of health (expressed in healthy life expectancy at 30) of various population groups –whites and Afro-Americans with different levels of education –growing inequalities are registered both between the two racial groups, and within themi Crimmings E and Saito Y (2001). (figures 2 and 3).
User fees in private non-for-profit hospitals in Uganda: a survey and intervention for equity
(BioMed Central Ltd., 2005) Amone Joseph; Asio Salome; Cattaneo Adriano; Kweyatulira Annet Kakinda; Macaluso Anna; Maciocco Gavino; Mukokoma Maurice; Ronfani Luca; Santini Stefano
Background: In developing countries, user fees may represent an important source of revenues for private-non-for-profit hospitals, but they may also affect access, use and equity. Methods: This survey was conducted in ten hospitals of the Uganda Catholic Medical Bureau to assess differences in user fees policies and to propose changes that would better fit with the social concern explicitly pursued by the Bureau. Through a review of relevant hospital documents and reports, and through interviews with key informants, health workers and users, hospital and nonhospital cost was calculated, as well as overall expenditure and revenues. Lower fees were applied in some pilot hospitals after the survey. Results: The percentage of revenues from user fees varied between 6% and 89% (average 40%). Some hospitals were more successful than others in getting external aid and government subsidies. These hospitals were applying lower fees and flat rates, and were offering free essential services to encourage access, as opposed to the fee-for-service policies implemented in less successful hospitals. The wide variation in user fees among hospitals was not justified by differences in case mix. None of the hospitals had a policy for exemption of the poor; the few users that actually got exempted were not really poor. To pay hospital and non-hospital expenses, about one third of users had to borrow money or sell goods and property. The fee system applied after the survey, based on flat and lower rates, brought about an increase in access and use of hospital services. Conclusion: Our results confirm that user fees represent an unfair mechanism of financing for health services because they exclude the poor and the sick. To mitigate this effect, flat rates and lower fees for the most vulnerable users were introduced to replace the fee-for-service system in some hospitals after the survey. The results are encouraging: hospital use, especially for pregnancy, childbirth and childhood illness, increased immediately, with no detrimental effect on overall revenues. A more equitable user fees system is possible.